Optimal Partitioning of Reconfigurable Intelligent Surfaces for Uplink NOMA Networks

In this work, we examine the potential of reconfigurable intelligent surfaces (RISs) to facilitate and enhance uplink (UL) transmissions in grant-free non-orthogonal multiple access (GF-NOMA) networks. The proposed RIS-assisted GF-NOMA approach employs virtual partitioning of RIS, with each partition tailored to optimize channel conditions for individual NOMA user equipment (UE). The resulting channel gain disparity bolsters the NOMA gain and obviates the necessity for UL power control of the grant-based NOMA schemes. Our approach is evaluated under three practical operational regimes: 1) quality-of-service (QoS) sufficient regime, 2) efficient RIS usage regime, and 3) max-min fair regime, all subject to UL-QoS constraints. We derive closed-form solutions to elucidate how optimal RIS partitioning can fulfill UL-QoS requirements across all three operational regimes. Comprehensive simulations are conducted to validate the precision of our analytical findings, demonstrating that the proposed approach substantially improves wireless communication system performance while mitigating signaling overhead and computational complexity.